Methods for scanning an examination subject by way of a CT system are generally known. For example, typical methods employed in such cases are circular scans, sequential orbital scans with patient feed-through, or spiral scans. Other types of scan that are not based on circular movements are also possible, such as e.g. scans with linear segments. Absorption data of the examination subject is acquired from different recording angles with the aid of at least one X-ray source and at least one oppositely located detector, and the thus collected absorption data or, as the case may be, projections are computed by means of appropriate reconstruction methods into sectional images (slices) through the examination subject.
In order to reconstruct computed tomographic images from X-ray CT data sets of a computed tomography device (CT scanner), i.e. from the acquired projections, a method referred to as filtered back-projection (FBP) is currently employed as the standard procedure. Following the data acquisition a so-called “rebinning” step is performed in which the data generated by means of the beam spreading out from the source in the shape of a fan is reordered in such a way that it is available in a form as though the detector had been impinged upon by X-ray beams converging in parallel onto the detector. The data is then transformed into the frequency domain. Filtering takes place in the frequency domain and subsequently the filtered data is back-transformed. A back-projection onto the individual voxels within the volume of interest is then performed with the aid of the thus re-sorted and filtered data.
Iterative reconstruction methods have recently been developed wherein initial image data is first reconstructed from the projection measured data. A convolution back-projection method, for example, can be used for this purpose. Synthetic projection data is then generated from said initial image data by means of a “projector”, that is to say a projection operator which is intended to mathematically map the measurement system as accurately as possible. The difference with respect to the measurement signals is then back-projected using the adjoint operator associated with the projector and in this way a residuum image is reconstructed and used to update the initial image. The updated image data can in turn be used in order to generate new synthetic projection data in a next iteration step with the aid of the projection operator, the difference with respect to the measurement signals can once again be formed therefrom, and a new residuum image can be computed and in turn used to enhance the image data of the current iteration step, etc. By way of such a method it is possible to reconstruct image data that provides relatively good image definition and nonetheless exhibits low image noise.
Different types of artifacts can appear in the CT images depending on conditions during the measured data acquisition and depending on the examination subject being studied in a particular case. Beam hardening artifacts are an example of this. These are produced due to the fact that the radiation emitted by the CT X-ray source is not monochromatic, but polychromatic, and that the attenuation of the X-ray radiation is dependent on its energy in a particular instance. Furthermore, different materials have different energy-dependent attenuation profiles. Artifacts are produced if this is not taken into account during the image reconstruction. This is particularly serious if components of the examination subject having high attenuation values are present.